Blood Features Associated with Viral Infection Severity: An Experience from COVID-19-Pandemic Patients Hospitalized in the Center of Iran, Yazd

Pandemics such as coronavirus disease 2019 (COVID-19) can manifest as systemic infections that affect multiple organs and show laboratory manifestations. We aimed to analyze laboratory findings to understand possible mechanisms of organ dysfunction and risk stratification of hospitalized patients in these epidemics. Methods. This retrospective study was conducted among patients admitted to COVID-19 referral treatment center, Shahid Sadoughi Hospital, Yazd, Iran, from April 21 to November 21, 2021. It was the fifth peak of COVID-19 in Iran, and Delta (VOC-21APR-02; B.1-617.2) was the dominant and most concerning strain. All cases were positive for COVID-19 by RT-PCR test. Lab information of included patients and association of sex, age, and outcome were analyzed, on admission. Results. A total of 466 COVID-19 patients were included in the study, the majority of whom were women (68.9%). The average age of hospitalized patients in male and female patients was 57.68 and 41.32 years, respectively (p < 0.01). During hospitalization, abnormality in hematological and biochemical parameters was significant and was associated with the outcome of death in patients. There was incidence of lymphopenia, neutrophilia, anemia, and thrombocytopenia. The changes in neutrophil/lymphocyte (N/L) and hematocrit/albumin (Het/Alb) ratio and potassium and calcium levels were significant. Conclusion. Based on these results, new biochemical and hematological parameters can be used to predict the spread of infection and the underlying molecular mechanism. Viral infection may spread through blood cells and the immune system.


Introduction
Te signs and symptoms of many viral diseases, including SARS-CoV-2, acute infuenza (H1N1/H5N1/H7N9), dengue fever, and human acquired immunodefciency virus (HIV) infection, are clinically very similar.However, reports about the underlying mechanism of organ injuries in these viral infections are still limited [1][2][3].It is unclear why severe illness and death occur only in a small subset of viral infections that primarily target the lungs of patients.However, in severe cases, it can damage other organs [2][3][4].
Laboratory changes in severe cases of fu and COVID-19 can be accompanied by acute respiratory syndrome (ARDS) and failure of vital organs such as the liver, kidney, and heart [5][6][7].
Tere is always the risk of the emergence of an infectious strain of a virus such as acute infuenza (H1N1/H5N1/ H7N9) and coronavirus disease 2019 (COVID-19) that can appear as a systemic infection and afect multiple organs and lead to critically ill patients.
Laboratory fndings are manifestations that show organ damage and dysfunction and help diagnose the severity of the disease and realize critically ill patients [2,3].
Tis study attempted to analyze and classify the laboratory fndings of severe COVID-19 infection in order to fnd new markers or indicators that can rapidly identify critically ill patients as well as to understand the molecular mechanism involved in severe infection and help in the disease treatment.
Previously, some laboratory fndings have been reported from COVID-19 cases; however, there are always new indicators that are better predictors of body dysfunction and ARDS [8][9][10].
Tis work tried to collect recorded data from patients hospitalized for COVID- 19 and analyze them to fnding and explaining new hematological/biochemical indicators related to vital organ function such as the kidney, liver, and heart where they are important for diagnosing/predicting COVID-19 courses.
Here, to provide further insight into the pathogenesis of viral infections and their severities, we analyzed the laboratory fndings of hospitalized patients with COVID-19.According to the reports in the literature and the parameters evaluated in the study, we tried to fnd a correlation between laboratory fndings and clinical complications (such as nephropathy and cardiovascular risk) caused by acute viruses such as SARS-CoV-2 [8][9][10].

Study Population and Design.
Te institutional review board of Payam Noor University of Taft, Yazd, and Head of Shahid Sadoughi Hospital, Yazd, Iran, approved this retrospective and Accountability Act-compliant review of existing medical records and waived the requirement for informed consent.
Collected data were from April 21 to November 21, 2021, at COVID-19 referral treatment center, Shahid Sadoughi Hospital, Yazd, Iran, from biochemical and hematological parameters assessed among admitted COVID-19 patients.It was the ffth peak of COVID-19 in Iran, and Delta (VOC-21APR-02; B.1-617.2) was the dominant and most concerning strain.Hospitalized patients who had RT-PCR positive test for COVID-19 and D-dimer test were included.All admitted patients met the following inclusion criteria mentioned by the Iranian national COVID-19-headquarter instructions and guidelines for COVID-19, Ministry of Heath, and the World Health Organization (WHO) criteria for COVID-19 [11,12].Ultimately, 466 COVID-19 hospitalized patients were selected and included.

Data Collection and Sampling.
Data were extracted from electronic records of COVID-19 patients refereed to COVID-19 referral treatment center from April 21 to November 21, 2021, and included demographic, clinical, and laboratory data.Blood samples had been collected from patients after admission for analysis of biochemical and hematological parameters, while diet restriction was monitored for 6 hours before sampling.Te laboratory records included creatinine (Cr) and urea levels, liver function tests, D-dimer, ferritin, C-reactive protein (CRP), and creatine kinase (CPK) levels, platelet counts, prothrombin time (PT) and activated partial thromboplastin time, hemoglobin (Hb) and complete blood count (CBC), white blood cell (WBC) concentration, red blood cell (RBC) and platelet count (PLT) tests, and electrolyte parameters (Ca 2+ , Na + , CI − , K + , and HCO 3 ).Neutrophil/lymphocyte (N/L) and hematocrit/albumin (Het/Alb) ratios were calculated as additional hematological parameters which may be used for fast diagnosis of severe infections [8,9,13].

Data Extraction and Statistical
Analysis.Electronic records of COVID-19 patients on admission were collected which included laboratory tests and demographic data during routine examination of patients at the hospital.We applied IBM SPSS software (version 22.0) for all statistical analyses.Continuous variables were tested for normality and are reported as mean ± standard deviation or median.
We assessed the correlations among diferent blood parameters using correlation analysis tests (Pearson's/ spearman coefcient, each was appropriate).Binary logistic regression model was used to estimate which biochemical and hematological abnormality can be used as an indicator of the occurrence of death in patients: biochemical cutofs as an independent variable and the outcome of death as a dependent variable.p value <0.05 was considered statistically signifcant.

Demographics of Admitted
Patients.In this study, clinical and laboratory data of electronic records of 466 hospitalized COVID-19 patients refereed to COVID-19 referral treatment center from April 21 to November 21, 2021, were included.Overall, 31% of admitted patients were male of whom 51% died (Tables 1(a)-1(c)).
Diferences in gender and age have an impact on patients' outcome, and male and old patients were, respectively, 2.99 and 2.62 times more at risk of death compared to patients without this condition (Table 1(a)).
Descriptive statistics for all COVID-19-hospitalized patients included in this study are provided in Tables S1-S5 in the supplemental data.Based on the outcomes of COVID-19-included subjects, 66.31% and 33.69% of patients recovered and did not recover in hospital (death outcome), respectively (Tables 1(a) and S3-S5).
Te average age of recovered patients and nonrecovered patients (deceased group) was 39.8 and 59.43 years, respectively (p < 0.001, Figure 1(a)).Te average age of male and female patients was 57.68 and 41.32 years, respectively (p < 0.001, Figure 1(b)).Te average age of recovered male and female patients was 55 and 35 years, respectively (p < 0.05, Figures 1(c) and 1(d)).

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International Journal of Clinical Practice   International Journal of Clinical Practice Among the hospitalized patients, 145 (31%) were male and 321 (68.9%) were female.In terms of disease severity, 51% of men and 25.9% of women died in hospital (p < 0.001, Table 1(a)).Regarding the age range of participants, 64.50% of female patients were between 18 and 40 years old and 35.50% of them were over 40 years of age (p ∼ < 0.000, Figure 1(e)), while 12.2% of male participants were under 40 years of age (p ∼ 0.05) and the majority of them were over 40 years of age (87.7%, p ∼ 0.051 (Figure 1(f )).

Blood Groups and Severity of COVID-19.
Frequency of blood groups among included patients was diferent but not found statistically signifcant compared to the normal frequency in the society.Te percentage of patients with blood group B (±) was higher than the normal percentage in the population (p ∼ 0.5, Table S1A).Binary logistic regression analysis showed the highest odds of death for AB blood group among COVID-19 patients (Table 1(c)).
Diabetes mellitus of admitted patients was signifcantly higher than the normal frequency in the society according to reference [14] and more common in female patients (p < 0.001, Table S1B).Diabetic patients were 2.574 times more at risk of progression to the deceased outcome compared to the patients without this disorder (Table 1(a)).
Patients with SGOT >40 were 2.174 times more at risk to progress to death than patients with SGOT ≤40 (p < 0.01, Table 1

(a)).
Patients who progressed to death showed signifcantly higher bilirubin D, alkaline-P, and ferritin levels than those who recovered (p < 0.05, Table S6).In patients with deceased outcome, bilirubin D levels showed a signifcant correlation with alkaline-P, PT, and PLT (p < 0.01, Table S18).Generally, bilirubin D >0.2 and alkaline-P >128 caused 7.347 and 1.518 times more risk of progression to the deceased outcome in COVID-19 patients, respectively (Tables 1(a) and S19A).

Some Laboratory Findings Related to Kidney Function.
Frequency of creatinine levels >1.4 was 13.1% in COVID-19 patients of whom 73.8% died in the hospital (p < 0.001, Table 1(a)).Male patients were 4.696 times more likely to sufer from creatinine>1.4than women (p < 0.001, Table S11).
Patients with hyperkalemia and hypocalcemia were 9.231 and 2.567 times more susceptible to progress to the deceased outcome, respectively (p < 0.001, Tables 1(a) and S19A).

Hematological Abnormalities in COVID-19 Patients.
Hematological characteristics of the patients on admission are presented in Tables S4 and S13.Patients who died in hospital showed signifcantly higher levels of WBC/neutrophils/CRP/ ferritin and PT than recovered patients (p < 0.01, Table S13).Compared with the recovered group with N/L and Het/Alb less than 8 and 9, the deceased group had N/L and Het/Alb more than 8 and 9, respectively (p < 0.01, Table S13).
Correlation analysis showed that neutrophil counts may be positively correlated with ferritin levels and negatively correlated with PT and PLT (p < 0.01, Tables 2 and S18).
Lymphopenia patients had higher levels of N/L and Het/ Alb ratios (Table S15).In patients with deceased outcome, lymphocyte correlated negatively with N/L ratio (p < 0.01, Tables 2 and S10).
Correlation analysis showed that RBC count may be positively correlated with Het/Alb ratio and Ca 2+ levels (p < 0.01, Tables 2, S10, and S18).
Te frequency of low hemoglobin levels was almost similar in male and female patients.Patients with hemoglobin <12 showed low levels of bilirubin T, hematocrit, MCH, and MCHC (p ∼ 0.782, Table S16).
In addition, COVID-19 patients with N/L index >9 and Het/Alb index >10 may be 5.59 and 1.295 times more prone to the progression to the death outcome, respectively (p < 0.01, Tables 1(c) and S19).

Discussion
Pandemics such as COVID-19 and acute infuenza (H1N1/ H5N1/H7N9) can manifest as systemic infections that afect multiple organs and show laboratory manifestations.Tere is always need for new biochemical and hematological indicators which can be used to predict the outcome of infection and the underlying molecular mechanism [2,3,9].
Tis retrospective study was conducted to analyze laboratory fndings of COVID-19 severe infection to understand possible mechanisms of organ dysfunction and risk stratifcation of hospitalized patients in these epidemics.
In this study, the prevalence of diabetes was high in hospitalized patients, the majority of whom was females (Table S1).
Low levels of albumin and Ca 2+ and increased levels of ferritin, LDH, CPK, SGOT, SGPT, bilirubin D, alkaline-P, urea, creatinine, Na + , and K + were observed in patients (Tables S6-S8).Te increase in CPK levels was signifcantly related to the increase in creatinine, urea, LDH, SGOT, and SGPT levels.Bilirubin D showed a positive correlation with alkaline-P, PLT, and PT (Table S18).In addition, the risk of death from viral infection was signifcantly associated with cutof levels of K + , creatinine, bilirubin D, urea, and Ca 2+ (odd ratio (OR) >3, Tables 1(a) and S18).
SARS-CoV-2 may directly bind to ACE2-positive cholangiocytes in the liver and cause liver abnormalities and damage [16].Human pancreatic islet cells, especially insulin-producing β-cells, widely express ACE2.ACE2 is also expressed by microvascular pericytes and pancreatic ductal cells, contributing to pancreatic secretion in the adaptive response to diet [17,18].We also found elevated levels of CPK without increase in troponin I that can be associated with focal myofbril necrosis and infltrating of infected macrophages [19,20].
In the alveolar region, macrophages, epithelial cells, and even endothelial cells express ACE2, and their activation through binding of ACE2 to the ligand leads to the release of proinfammatory cytokines, interleukin (IL)-1β and IL-18, and in short, the pathogenic Infammatory responses.In addition, the virus and its particles are recognized by other receptors expressed on professional antigen-presenting cells (APCs), mainly dendritic cells and macrophages.Trough these receptors, the virus enters APCs and may be transferred to CD4+ T cells via MHC II presenters [23,24], thereby inducing IL-6 overexpression and lymphocyte apoptosis [5].Overactivated macrophages may cause a hyper-infammatory life-threatening syndrome, associated with high levels of ferritin and CRP in the serum.Overactivated macrophages phagocytose red blood cells, leading to severe peripheral blood cytopenia, a common feature seen in the COVID-19 syndrome [25].Te cytokine storm and uncontrolled infammation are possible factors for neutrophilia and thrombocytopenia, which are associated with capillary and acute thrombosis [1,5,7].
Te virus may infect lymphocytes or hematopoietic stem cells (HSCs) in the bone marrow directly because they may express spike receptor (e.g., ACE2) on their surface [7,26,27].Infuenza and HIV agents to spread in the host body use a similar mechanism.HIV can infect HSCs as they express receptors of the virus.Abnormalities in ferritin and cytokine release and blood cell counts may be at least partially due to this mechanism [7,9,26].Erythrocytes express surface receptors that may act as attachment sites for infectious agents (such as HIV-1) to attack and kill cells [18,22,26].Specifc antigens on the surface of red blood cells can cause the direct or indirect transfer of the virus to the target cells and the spread of the virus in the body and cause susceptibility to the disease [28,29].
Finally, we found a signifcant association between gender, age, and diabetes with the increased risk of mortality in hospitalized patients with COVID-19, which may be related to the easy spread of the virus in the body, dysfunction of the cellular immune system, and long-term infammation in the elderly patients [15,20,26].
Tere are some suggestions for new biomarkers to accurately diagnose the disease and predict organ dysfunction.For example, high serum levels of proinfammatory cytokines (e.g., tumor necrosis factor-α (TNF-α), IL-6, and interferon-c (IFN-c)) and their associations with miRNA biomarkers may be useful as a prognostic marker in the management and early identifcation of patients at risk (Table 3) [30,36,37,52,54].
In pathological conditions, organs or blood cells secrete vesicles enriched in specifc miRNAs with important role in clinical and preclinical application [31,32,50].
Terefore, monitoring these miRNA patterns (Table 3) along with biochemical and hematological parameters may serve as a prognostic marker in the management and early identifcation of high-risk patients who require intensive care.
However, there are limitations in the present work since it is a retrospective study on data recorded from biomarkers measured in COVID-19 hospitalized patients.
Data from patients' follow-up after being discharged from the hospital and measuring more molecular biomarkers can enrich the study and help in more reliable interpretation of the results.

Conclusions and Recommendations
Comprehensive information about viral infections is important for early disease diagnosis, prevention of disease severity, and treatment planning.Tere are some similarities in the pathogenesis and laboratory manifestations of viral epidemics such as infuenza viruses and COVID-19 that may help in understanding the mechanisms of the disease and the severity.Acute infuenza (H1N1/H5N1/H7N9) and COVID-19 have appeared as a systemic infection in severe cases that afects multiple organs and shows life-threatening syndrome.
Data analysis and classifcation of laboratory fndings may help to elucidate new markers or indicators for the rapid diagnosis of severe cases of the disease, as well as for a better understanding of the molecular mechanism involved in organ dysfunction or abnormality.International Journal of Clinical Practice Fateme Sadeghi-Nodoushan and Fatemeh Pourrajab were responsible for project administration and prepared the original draft.7: some laboratory fndings of hospitalized patients on admission with SGOT/SGPT higher than the normal (SGOT >40 and SGPT >56) and its association with sex and age (n � 466).Table 8: some laboratory fndings of hospitalized patients on admission with SGOT/SGPT higher than the normal (SGOT >40 and SGPT >56) and its association with sex and age (n � 466).Table 9A: the magnitude of CPK >200 in hospitalized patients, on admission, and its association with sex.
Table 9B: some laboratory fndings of hospitalized patients, on admission, with diferent levels of CPK> <200 and its association with sex and age.Table 10: some laboratory fndings of hospitalized patients on admission with different serum levels of CPK> ≤200 and its association with deceased outcome.Table 11: the magnitude of some biochemical abnormalities in hospitalized patients, on admission, and its association with sex.Table 12A: some laboratory fndings of admitted patients showing serum levels of creatinine >1.4.Table 12B: some laboratory fndings of admitted patients showing serum levels of creatinine >1.4, and its association with age.Table 13A: comparison of some hematological parameters between two recovered and nonrecovered groups of COVID-19 hospitalized patients, on admission (n � 466).Table 13B: comparison of some hematological parameters between two recovered and nonrecovered groups of COVID-19 hospitalized patients, on admission (n � 466).Table 14: the magnitude and laboratory fndings of some hematological abnormalities in hospitalized patients on admission and the association with sex.Table 15A: some laboratory fndings of admitted patients with lymphocyte counts ≥<1.Table 15B: some laboratory fndings of admitted patients with lymphopenia (<1) and its association with deceased outcome.Table 16A: the magnitude and laboratory fndings of hemoglobin <12 in hospitalized patients on admission and the association with sex.Table 16B: some laboratory fndings of admitted patients with serum levels of hemoglobin ≥<12.Table 17: some laboratory fndings of admitted patients with hemoglobin ≥<12 and its association with deceased outcome.Table 18: correlations between biochemical parameters in COVID-19 patients with recovered or deceased outcomes.Table 19A: multivariate analysis of biochemical factors and infammatory markers that might be associated with COVID-19 risk of death.Table 19B: multivariate analysis of infammatory markers that may be associated with COVID-19 risk of death.Table 19C: multivariate analysis of hematological factors that may be associated with COVID-19 risk of death.Table 20A: multivariate analysis for the association of age with lymphopenia and neutrophilia in COVID-19 admitted patients (n � 466).Table 20B: multivariate analysis for the association of age with lymphopenia and neutrophilia in COVID-19 admitted patients (n � 466).(Supplementary Materials)

Figure 1 :
Figure 1: Sex and age characteristics of admitted COVID-19 patients and outcomes, at COVID-19 referral treatment center, Shahid Sadoughi Hospital, Yazd, Iran (women, n � 309; men, n � 157).(a) Te average age of recovered and nonrecovered patients (deceased group) was 39.8 and 59.43 years, respectively.(b) Te average age of male and female patients was 57.68 and 41.32 years, respectively.(c, d) Te average age of the deceased group in males and females was 60.84 and 58.17 years, respectively.(e) In the age range of female participants, 64.50% of them were between 18 and 40 years old.(f ) In the age range of male participants, 12.2% were under 40 years old, and 87.7% were over 40 years old.
a Patient data were divided into two categories: those who died in the hospital and those who were discharged from the hospital, and then the information was analyzed by logistic regression to identify possible potential risk factors.Te cutofs were selected according to the normal range of biochemical markers.bPatientsweredividedintotwo categories: those who died in the hospital and those who were discharged from the hospital, and then their frequencies in each group were analyzed and compared.cTelogisticregressionanalysiswas done to estimate which indicator can be related to the occurrence of death in patients: biochemical cutofs as independent variables and the outcome of death as a dependent variable.*≤:theserumrangesequal to or less than the normal reference range.**≥: the serum ranges equal to or more than the normal reference range.FBS: fasting blood sugar; SGOT: serum glutamate-pyruvate aminotransferase; GPT: serum glutamate-oxaloacetate aminotransferase; CPK: creatine kinase.dPatientsweredividedintosubgroups based on specifc cutof of each variable that showed associations with the deceased outcome including hemoglobin (cutof <12), anemia (cutof <3.5), neutrophilia (cutof >8), lymphocytopenia (cutof <1), thrombocytopenia (cutof <140), prothrombin time (PT) (cutof <13), and blood groups (A−/A+, AB−/AB+, B−/B+, and O−/O+).ePatientsweredividedintotwocategories: those who died in the hospital and those who were discharged from the hospital, and then their frequencies in each group were analyzed and compared.fTelogisticregressionanalysiswas done to estimate which indicator can predict the occurrence of death in patients: hematological cutofs as an independent variable and the outcome of death as a dependent variable.gCaseswithRBCcount <3.5 × k Cases with prothrombin time (sec).lPatientswere divided into subgroups based on a specifc cutof of each variable that showed associations with the deceased outcome including N/L ratio (cutof >9), D-dimer (cutof >200), CRP (cutof∼ +1, +2, +3), ferritin (cutof >300), and Het/Alb index (cutof >10).mPatients were divided into two categories: those who died in the hospital and those who were discharged from the hospital, and then their frequencies in each group were analyzed and compared.nTelogistic regression analysis was done to estimate which indicator can be related to the occurrence of death in patients: biomarker cutof as an independent variable and the outcome of death as a dependent variable.N/L: neutrophil/lymphocyte; CRP: C-reactive protein; Het/Alb: hematocrit/albumin.o

Table 2 :
Possible correlations between hematological and biochemical parameters in two groups of COVID-19 patients.
a Patients were divided into two groups: those who died in the hospital (deceased group) and those who were discharged from the hospital (recovered group), and then the possible correlations between hematological and biochemical parameters were evaluated in each group, separately.*Correlation is signifcant at the 0.05 level (2-tailed).**Correlation is signifcant at the 0.01 level (2-tailed).Hb: hemoglobin; RBC: red blood cell; Alb: albumin; N/L: neutrophil/lymphocyte; Het/Alb: hematocrit/albumin; WBC: white blood cell count; PLT: platelet count; PDW: platelet distribution width; Ca: calcium.8InternationalJournal of Clinical Practice

Table 3 :
Circulating biomarkers and associated miRNAs related to organ dysfunction and abnormalities in COVID-19.